Spatiotemporal correlation of urban pollutants by long-term measurements on a mobile observation platform. (1st January 2021)

• Record Type: Journal Article
• Authors: Crocchianti, Stefano; Del Sarto, Simone; Ranalli, Maria Giovanna; Moroni, Beatrice; Castellini, Silvia; Petroselli, Chiara; Cappelletti, David
• Is Part Of: Environmental pollution. Volume 268(2021)Part A
• Publication Date: 2021-01-01
• Subjects: Cable train measurement platform -- Size segregated particulate matter -- Nitrogen monoxide -- Spatiotemporal structure -- Vehicular traffic; Pollution -- Periodicals; Pollution -- Environmental aspects -- Periodicals; Environmental Pollution -- Periodicals; Pollution -- Périodiques; Pollution -- Aspect de l'environnement -- Périodiques; Pollution -- Effets physiologiques -- Périodiques; Pollution; Pollution -- Environmental aspects; Periodicals; Electronic journals; 363.73
• DOI: 10.1016/j.envpol.2020.115645
• Languages: English
• ISSNs: 0269-7491

Abstract

Abstract: We conducted a three-year campaign of atmospheric pollutant measurements exploiting portable instrumentation deployed on a mobile cabin of a public transport system. Size selected particulate matter (PM) and nitrogen monoxide (NO) were measured at high temporal and spatial resolution. The dataset was complemented with measurements of vehicular traffic counts and a comprehensive set of meteorological covariates. Pollutants showed a distinctive spatiotemporal structure in the urban environment. Spatiotemporal autocorrelations were analyzed by a hierarchical spatiotemporal statistical model. Specifically, particles smaller than 1.1 μm exhibited a robust temporal autocorrelation with those at the previous hour and tended to accumulate steadily during the week with a maximum on Fridays. The smallest particles (mean diameter 340 nm) showed a spatial correlation distance of ≈ 600 m. The spatial correlation distance reduces to ≈ 60 m for particle diameters larger than 1.1 μm, which also showed peaks at the stations correlated with the transport system itself. NO showed a temporal correlation comparable to that of particles of 5.0 μm of diameter and a correlating distance of 155 m. The spatial structure of NO correlated with that of the smallest sized particles. A generalized additive mixed model was employed to disentangle the effects of traffic and other covariates on PM concentrations. A reduction of 50% of the vehicles produces a reduction of the fine particles of −13% and of the coarse particle number of −7.5%. The atmospheric stability was responsible for the most significant effect on fine particle concentration. Graphical abstract: Image 1 Highlights: Fine particles correlate with 4 h cumulated traffic up to ∼600 m in the city. Coarse particles have a correlation distance of 60 m. Nitrogen monoxide shows a spatial correlation distance of 155 m. The spatiotemporal structure of nitrogen monoxide correlates better with fine particles. a 50% vehicular traffic reduction results in a 13% decrease of fine particles.